Agile Data

Why Agile Data?

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The purpose of this site is to share leading edge techniques for data-related software development issues. Data is clearly an important aspect of any business system, and data management is a critical task for all organizations, so therefore data-related issues are something that all software professionals must take into consideration.

Over the years I have written a fair amount about how to use object and relational database technology together, and in general how application developers and data professionals can work together effectively. At the technical level I wrote some of the seminal work in the early to mid-90s around mapping objects to RDBs and how to design object persistence layers for RDBs. I've also written several books that covered critical object/data issues, including The Object Primer 3/e which describes how to build business applications from the point of view of a developer and co-authored Mastering EJB 2/e (I wrote the complex persistence material). In both of those books I apply the Unified Modeling Language (UML) for data modeling. I also co-wrote Refactoring Databases: Evolutionary Database Design which addresses how DBAs can evolve database schemas just as application developers evolve their object schemas. I've also written about cultural/organization-related as well, in particular the articles The Cultural Impedance Mismatch Between Data Professionals and Application Developers.

I believe that we need to find ways to work together effectively, and that there are five fundamental tasks which IT organizations must undertake:

  1. Adopt a new philosophical foundation. The Agile Data Method, and the supporting agile database techniques, describe an approach that has a chance at succeeding because it describes ways that people actually work in practice. It’s not just a collection of academic theories that sound great. The heart of the Agile Data method is in its philosophies and its roles. The philosophies sound simple yet in practice have significant implications when you act on them: my experience is that rethinking your approach to software development and reworking your organization's culture to succeed at the software development game will prove to be difficult in practice.

  2. Help both developers and data professionals need to adopt evolutionary, if not agile, database techniques. This includes agile data modeling, database refactoring, database regression testing, test-driven development (TDD), and encapsulating database access appropriately. We must all recognize we need to become more agile, that we can take an agile approach to modeling and documentation, that data models don't drive object models (and vice versa), that we need new tools, and that we should work in our our separate development sandboxes. Adopting common agile database core practices is also a very good idea.

  3. Help developers learn fundamental data techniques. This includes data modeling, mapping objects to RDBs (O/R mapping), and working with legacy data. Developers should also understand how to choose a primary key strategy for a table, relational database fundamentals, referential integrity and shared business logic, how to retrieve objects from an RDB, how to implement reports, security access control, transaction control, and concurrency control.

  4. Help data professionals to learn fundamental development techniques. This includes learning the basics of object orientation and the Unified Modeling Language (UML) and how to data model using the UML.

  5. Take an agile approach to enterprise efforts. Your enterprise architecture and enterprise administration (including operational data administration) groups need to become more agile to succeed in modern IT environments. It's not only possible to take an agile enterprise approach, I believe it's preferable to traditional traditional techniques because it's more responsive to the actual needs of your organization.

In short, this site is dedicated to sharing effective practices, not questionable theories.